Automatic gain control (AGC) systems are generally designed to provide a normalized speech level at the output of the system by applying a gain to voice signals received at an input. It is typically desirable that this gain is made as a function of time and that this gain is varied very slowly from one frame to another. However, if the gain that will be applied to speech signal is high, then it will take very long time for AGC to settle to the normalized desired speech level. Unfortunately, many previous AGC algorithms suffered in effectiveness by providing normalized speech very quickly without considering the level of speech signal at the input.
Another problem with previous AGC systems involves noisy environments such as automobile applications. In these applications, where background noise is often high, communications sometimes become impossible when AGC algorithms amplify noise signals more than speech signals. This is a considerable problem in vehicle-to-vehicle communications, which results in an increased noise loop back problem from one vehicle to another, often making effective communications difficult or impossible to achieve.
Still another problem associated with previous AGC approaches is the tendency to over or under amplify the input signal under certain conditions, creating a non-desirable output. More specifically and when normalizing audio signals, unintentional over-amplification can produce a noticeably unpleasant (e.g., noisy) output. When used in vehicle-based hands-free applications where an AGC algorithm is intended to normalize speech, over amplified signals can be unintentionally produced by noise and other sounds common to the environment in the input signal that are misrecognised as speech.
The problems described above result in the limited use of AGC algorithms in automobile and other noisy applications. And when used, user dissatisfaction with these approaches has been high.
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